Established in 2006, TATA Africa Services (Nigeria) Limited operates as the nodal point for Tata businesses in West Africa. TATA Africa Services (Nigeria) Limited has a strong presence in Nigeria with investments exceeding USD 10 million. The company was established in Lagos, Nigeria as a subsidiary of TATA Africa Holdings (SA) (Pty) Limited, South Africa and serves as the hub of Tata’s operations in Nigeria and the rest of West Africa.

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Covid-19′s impact on supply chain decisions: Strategic insights from NASDAQ 100 firms using Twitter data

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.,To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.,As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.,This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.,This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.

Adoption of AI-based chatbots for hospitality and tourism.

The importance of text mining is increasing in services management as the access to big data is increasing across digital platforms enabling such services. This study adopts a systematic literature review on the application of text mining in services management. First, we analyzed the literature on which has used text mining methods like Sentiment Analysis, Topic Modeling, and Natural language Processing (NLP) in reputed business management journals. Further, we applied visualization tools for text mining and the topic association to understand the dominant themes and relationships. The analysis highlighted that social media analysis, market analysis, competitive intelligence are the most dominant themes while other themes like risk management and fake content detection are also explored. Further, based on the analysis, future research agenda in the field of text mining in services management has been indicated.

Applications of text mining in services management: A systematic literature review

Transaction prices represent one of the most attractive -- and overlooked -- opportunities to boost profits The fastest and most effective way for a company to realize its maximum profit is to get its pricing right. The right price can boost profit faster than increasing volume will; the wrong price can shrink it just as quickly. Without realizing it, however, many managers are leaving significant amounts of money -- potential profit -- on the table at the transaction level, the point where the product meets the consumer.(*) Most companies use invoice price as a reporting measure, but the differences between invoice and actual transaction price can mean significant reductions to bottom-line profit. Some companies that have identified this problem are handling it by applying two basic concepts: the pocket price waterfall and the pocket price band. Reduced to their essentials, these concepts show companies where their products' prices erode between invoice price and actual transaction price, and they help companies capture untapped opportunities at that level. THE LEVERAGE and payoff of improved pricing are high. Compare, for example, the profit implications of a 1 percent increase in volume and a 1 percent increase in price. For a company with average economics, improving unit volume by 1 percent yields a 3.3 percent increase in operating profit, assuming no decrease in price. But, as Exhibit 1 shows, a 1 percent improvement in price, assuming no loss of volume, increases operating profit by 11.1 percent. Improvements in price typically have three to four times the effect on profitability as proportionate increases in volume. With such extreme profit leverage, pricing is one function that a company can always improve. One consumer durable products company increased operating profit dollars by nearly 30 percent with a mere 2.5 percent improvement in average prices. An industrial equipment manufacturer boosted operating profits by 35 percent by carefully managing price levels up a modest 3 percent. According to our research, a wide variety of businesses, including those in consumer packaged goods, energy, and banking and financial services, have achieved comparable results. Even if a company's managers make the right pricing decisions 90 percent of the time, it's worthwhile to try for 92 percent -- the payoff is that high. But the price lever is a double-edged sword. The messages of Exhibit 1 also apply in reverse: a mere 1 percent price decrease for an average company, for instance, would destroy 11.1 percent of the company's operating profit dollars. Pricing issues are seldom simple and isolated; usually they are diverse, intricate, and linked to many aspects of a business. But while most managers have a handle on the bulk of pricing issues, many overlook a key aspect of this most basic management discipline: transaction price management. The three levels of price management The pricing puzzle is more manageable when taken in pieces. Price management issues, opportunities, and threats fall into three distinct but closely related levels: 1. Industry supply and demand. At this highest level of price management, the basic laws of economics come into play. Changes in supply (plant closings, new competitors), demand (demographic shifts, emerging substitute products), and costs (new technologies) have very real effects on industry price levels. Managers examining pricing in this context should understand the pricing "tone" of their markets -- that is, the overall direction of price pressure (up or down) and the critical marketplace variables fueling that pressure. This knowledge allows managers not only to predict and exploit broad price trends but also to foresee the likely impact of their actions on industry price levels. 2. Product market strategy. The central issue here is how customers perceive the benefits of products and related services across available suppliers. …

Managing Price, Gaining Profit

This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing.,In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), as the basis of the mixed method. STM was used to discover the evolution of topics over time. Moreover, bibliometrics (and network analysis) were used to highlight IJCHM’s top researchers, top-cited references, the geographical networks of the researchers and differences in the collaborative networks.,The number of papers published continually increased over time with changes of key researchers publishing in IJCHM. The co-authorship networks have also changed and revealed an increasing diversity of authorship and collaborations among authors in different countries. Moreover, the variety of topics and the relative weight of each topic have also changed.,Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided.,It is the first attempt to apply topic modeling to a leading academic journal in hospitality and tourism and explore the diversity in contemporary hospitality management research (topics and contributors) from 30 years of published research.

30 years of contemporary hospitality management

Corporate social responsibility (CSR) is an essential business practice in industry and a popular topic in academic research. Several studies have attempted to understand topics or categories in CSR contexts and some have used qualitative techniques to analyze data from traditional communication channels such as corporate reports, newspapers, and websites. This study adopts computational content analysis for understanding themes or topics from CSR-related conversations in the Twitter-sphere, the largest microblogging social media platform. Specifically, a probabilistic topic modeling-based computational text analysis framework is introduced to answer three questions: (1) What CSR-related topics are being communicated in the Twitter-sphere and what are the prevalent topics or themes in CSR conversation? (topic prevalence); (2) How are those topics interrelated? (topic correlation); (3) How have those topics changed over time? (topic evolution). The topic modeling results are discussed, and the direction for future research is presented.

Corporate Social Responsibility (CSR): A Survey of Topics and Trends Using Twitter Data and Topic Modeling

Online communities are playing a critical role in social communication during the COVID-19 pandemic. We reviewed 25,795 online comments from Reddit, a popular social-media website with a subsection...

https://www.tandfonline.com/doi/pdf/10.1080/13683500.2020.1823336

Eunhye Park

Papers

30 years of contemporary hospitality management

Corporate Social Responsibility (CSR): A Survey of Topics and Trends Using Twitter Data and Topic Modeling

Tracking tourism and hospitality employees’ real-time perceptions and emotions in an online community during the COVID-19 pandemic

Tourism demand forecasting with online news data mining

Exploring user-generated content related to dining experiences of consumers with food allergies